2
Factors Contributing to U.S. Crime Trends

Alfred Blumstein and Richard Rosenfeld


Over the past 30 years, crime has become a major issue of public concern, of political discussion and action—often intemperate and not likely to reduce crime—and of major public expenditure. Despite its salience in the public arena, very little is known about the factors driving the crime trends, and the knowledge base is too limited to support intelligent forecasts of the direction in which crime rates are moving, especially when changing direction. Developing such a knowledge base is important for enhancing the rationality of public policies and public expenditures related to crime, particularly because many such commitments have to be made well in advance of their actual use. These include, for example, recruiting and training police forces, building prisons, and developing other interventions outside the criminal justice system.

In this chapter we summarize the crime trend history over the past 35 years, examine the factors that appear to have been particularly influential in driving those trends, consider whether change in those factors could have been known in advance, and use that information to indicate some of the potential directions for enhancing the knowledge needed for better explanations and forecasts.

One can expect that different crimes will be affected by different factors. In particular, one might anticipate that property crimes would be responsive to the state of economic opportunity, whereas violent crimes might be responsive to the availability of guns or to societal factors stimulating conflict. Many of these factors would be difficult to know in advance to warrant their serving as leading indicators to indicate future trends. The one factor that is often important in affecting crime is population composi-



The National Academies | 500 Fifth St. N.W. | Washington, D.C. 20001
Copyright © National Academy of Sciences. All rights reserved.
Terms of Use and Privacy Statement



Below are the first 10 and last 10 pages of uncorrected machine-read text (when available) of this chapter, followed by the top 30 algorithmically extracted key phrases from the chapter as a whole.
Intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text on the opening pages of each chapter. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.

Do not use for reproduction, copying, pasting, or reading; exclusively for search engines.

OCR for page 13
2 Factors Contributing to U.S. Crime Trends Alfred Blumstein and Richard Rosenfeld Over the past 30 years, crime has become a major issue of public con- cern, of political discussion and action—often intemperate and not likely to reduce crime—and of major public expenditure. Despite its salience in the public arena, very little is known about the factors driving the crime trends, and the knowledge base is too limited to support intelligent forecasts of the direction in which crime rates are moving, especially when changing direction. Developing such a knowledge base is important for enhancing the rationality of public policies and public expenditures related to crime, particularly because many such commitments have to be made well in advance of their actual use. These include, for example, recruiting and training police forces, building prisons, and developing other interventions outside the criminal justice system. In this chapter we summarize the crime trend history over the past 35 years, examine the factors that appear to have been particularly influential in driving those trends, consider whether change in those factors could have been known in advance, and use that information to indicate some of the potential directions for enhancing the knowledge needed for better explanations and forecasts. One can expect that different crimes will be affected by different factors. In particular, one might anticipate that property crimes would be respon- sive to the state of economic opportunity, whereas violent crimes might be responsive to the availability of guns or to societal factors stimulating conflict. Many of these factors would be difficult to know in advance to warrant their serving as leading indicators to indicate future trends. The one factor that is often important in affecting crime is population composi- 

OCR for page 13
 UNDERSTANDING CRIME TRENDS tion: Different demographic groups, particularly different age and ethnic groups, display very different rates of involvement in crime. Some of these factors could be addressed in the context of generating policies intended to reduce crime. For example, to the extent that unem- ployment among teenagers and young adults is a major contributing factor to the crimes they commit, then efforts at providing job assistance, job training, or extending unemployment support for those groups could well be stimulated by their anticipated crime trends. ANALYSIS OF SOME RECENT CRIME TRENDS1 We begin by examining trends in violent crimes, which are the most serious crimes and attract the greatest public concern. We focus on rob- bery and murder, the two violent crimes that are best measured. We devote less attention to the other two violent crimes, forcible rape and aggravated assault, both of which exhibit important measurement problems. Aggra- vated assault is troubled by the room for discretion in classifying an assault as either “aggravated” or “simple”; only if it is aggravated is it recorded as a Part I crime in the Federal Bureau of Investigation’s Uniform Crime Reports (UCR). Moreover, comparisons with the assault trends measured in the National Crime Victimization Survey (NCVS) suggest that the police have “upgraded” the recording and classification of assaults over time and classify many as aggravated that they would have treated as lesser offenses in the past (Rosenfeld, 2007a). The measurement of forcible rape is subject to important variations in whether the incident is reported to the police and counted as a Part I crime. Trends in Robbery and Murder In Figure 2-1 we compare the rates of homicide and robbery from 1972 to 2006. To provide a comparison of the two trends, we have divided the robbery rate by 25 to put robbery and murder on a comparable scale. The first observation from comparing the murder and robbery trends is their striking similarity. Both reach their peaks and their troughs within a year of each other. This may suggest that similar factors are affecting both trends, but not necessarily. It also is possible that one is driving the other. Explaining the correspondence between trends in different types of crime is an important issue for future research (see LaFree, 1998). 1 Exceptwhere indicated otherwise, we use the term “trends” in this chapter to refer to year- to-year variation in crime rates and associated conditions.

OCR for page 13
 FACTORS CONTRIBUTING TO U.S. CRIME TRENDS 12 Robbery/25 10 Rate per 100k Population 8 Murder 6 4 2 1970 1975 1980 1985 1990 1995 2000 2005 2010 Year FIGURE 2-1 Trends in murder and robbery, 1972-2006. Figure 2-1 Turning Points It is useful to examine the peaks and the troughs of these two curves as a way of identifying knowledge about the factors contributing to crime trends. The turning points are of particular interest because, once a trend has been established, the value for the current year and the current trend often yield a good prediction of the value for the next year. But the turning points are usually not easy to predict without a strong model of the factors accounting for such changes in direction. 0 and Age Composition There was an important turning point in 1980. The rather steady rise in both rates until 1980 can be attributed to factors associated with the postwar baby boom that began with the 1947 birth cohort. As the baby boom cohorts moved into the high-crime ages of about 15 to 20, they were important contributors to the crime rise of the 1960s and 1970s. This was a consequence of there being more people in those high-crime ages and also perhaps a cohort-size effect, whereby a larger cohort in those ages stimu- lated more of its members to engage in crime (Easterlin, 1987; O’Brien, Stockard, and Isaacson, 1999). The peak cohort in the baby boom era is the 1960 cohort, which had about 4.5 million members. By 1980 that

OCR for page 13
 UNDERSTANDING CRIME TRENDS group and large fractions of the baby boom population were moving out of the high-crime ages. Indeed, a detailed analysis of demographic effects on crime rates published in 1980, and therefore based on data for the 1970s, forecast that crime rates would peak in 1980 (Blumstein, Cohen, and Miller, 1980). Of course, that forecast was relatively easy to make because demo- graphic factors can be reliably traced well into the future, and indeed they are among the few factors that can easily be used as a leading indicator of crime rates.  and the Recruitment of Young People into Crack Cocaine Markets A second turning point in robbery and murder trends took place in 1985. Crime rates declined between 1980 and 1985, the decreases associ- ated with the demographic trends already identified. There was no prior expectation that crime rates would turn up after 1985. Undoubtedly, some other factor emerged that overwhelmed the continuing demographic trend. A detailed account (Blumstein, 1995; Blumstein and Rosenfeld, 1998) highlighted the importance of the recruitment of young people into crack markets as replacements for the older sellers who were being sent to prison at a very high rate in the early 1980s. Because crack was typically sold in street markets, these young sellers had to carry guns to protect themselves against street robbers (Jacobs, 2000). They were far less restrained then their older predecessors in the use of guns, and that diminished restraint contributed to a major rise in firearm violence. The violence was augmented by the tight networking of these young people, resulting in other young people with no involvement in drug markets arming themselves for self- defense or for the status derived from carrying a gun (Fagan and Wilkinson, 1998; Sheley and Wright, 1995). Popular accounts at the time directed attention to crack as an important factor in violent crime. The street markets were located in inner-city neigh- borhoods, where violence was a norm for dispute resolution (Anderson, 1999), and it arrived with widespread appeal, particularly for poor people who could not afford powder cocaine but could readily afford the low cost of crack, typically sold in small quantities. The “high” associated with crack is short-lived, 8-15 minutes, necessitating frequent purchases by regu- lar users. The high-volume street trade facilitated violence by street robbers who preyed on sellers and buyers, conflicts among sellers, and robberies by users seeking funds to purchase the drug (Jacobs, 1999). Although it was widely recognized that violence was associated with crack markets, it would have been difficult to know precisely when the turning point would occur. Crack markets began in Miami, New York, Los Angeles, and other larger coastal cities in the early 1980s, but the turning point did not occur until the major recruitment of the young replacements,

OCR for page 13
 FACTORS CONTRIBUTING TO U.S. CRIME TRENDS rather than with the introduction of crack. This effect is not very likely to have been anticipated in advance.  and the Decline in Demand for Crack by New Users The third major turning point depicted in Figure 2-1 occurred about 1993, which was the start of the major downturn documented in The Crime Drop in America (Blumstein and Wallman, 2006; see also Zimring, 2006). That book discusses the shrinkage in crack markets that resulted from a major drop in demand for crack by new users and the consequent departure from the crack markets of the young recruits (Johnson, Golub, and Dunlap, 2006). A robust economy could absorb those young people; unemployment rates for African-American teenagers reached 20- to 30-year lows by the mid-1990s (Nasar, 1998; Nasar and Mitchell, 1999). Between 1992 and 2000, unemployment dropped by 30 percent among African Americans without a high school diploma and by over 50 percent among similarly situated Hispanics (U.S. Census Bureau, 2006). Aggressive policing focused on young people with guns probably also contributed to the violent crime drop, although the effects of such programs have been documented for only a few cities (e.g., Kennedy et al., 2001). Another contributor was the continued drop in violent crime by people over 30, resulting in part from the growing prison population (Blumstein, 2006; Rosenfeld, 2006a). During the 1990s, the median age of state prisoners reached the early 30s, which criminal career research sug- gests is the age with the longest residual career following a criminal justice intervention. Thus, the departure of young people from the crack markets combined with the continuing decline of violence by the over-30 population were major factors contributing to the steady decline in violent crime from about 1993 until 2000. The role of aggressive policing of young people with guns or of other innovative policing strategies introduced during the decade is less easy to identify strongly (Eck and Maguire, 2006; Rosenfeld, Fornango, and Baumer, 2005). 000 and the End of the Crime Drop The year 2000 was not quite a turning point in the sense that it showed a trough in the crime rate, but it was certainly a turning point in convert- ing the steady decline of the 1990s to a very flat trend that continued at least until 2005. It is not surprising that the strong downward trend of the 1990s finally flattened out, but at the time it was not at all clear when that flattening would occur. The fact that the crime drop continued until 2000, resulting in low crime rates that had not been seen since the 1960s, was fortunate but not readily predictable.

OCR for page 13
 UNDERSTANDING CRIME TRENDS The Blip in 00 That flat trend continued over the next few years, with no changes greater than 2.5 percent. The increases continued through 2006, but in 2007 homicide and robbery rates decreased by 1.3 percent and 1.2 percent respectively (http://www.fbi.gov/ucr/cius2007/data/table_01a.html). These small changes do little to encourage a belief that neither the two previous increases nor the following decrease in 2007 represent any more than fluc- tuations around a continuing flat trend (Police Executive Research Forum, 2006, 2007; Rosenfeld, 2007b). It is easy to identify a number of factors that could be contributing to a new upward trend in violent crime, including: • reduced job opportunities for young people with minimal education, • reduced social services as a result of federal funding cuts, • reductions in the size of police forces, • diversion of police attention to terrorism issues, • slower growth in the prison population, and • diminished attention to gun control. The problem is that one could have enumerated these same factors in at least several of the preceding years or in 2007. Why they should be par- ticularly relevant in 2005 or 2006 is part of the dilemma of whether there is currently merely a blip or the start of a clear upward trend in violent crime. Trends in Burglary and Motor Vehicle Theft We have been examining just the trends in murder and robbery, the two most well-defined and well-measured violent crimes. Among property crimes, burglary and motor vehicle theft are of particular interest because of their seriousness, prevalence, and reliable measurement in the UCR. Well over half of burglaries documented in the NCVS are reported to the police, compared with only 32 percent of larcenies (http://www.albany.edu/ sourcebook/tost_3.html#3_x). Victims are even more likely to report motor vehicle thefts, partly because they depend on the police to recover their car and partly because of insurance requirements. But an important and poorly understood source of heterogeneity in motor vehicle theft is the large frac- tion of vehicles stolen for “joyriding” as opposed to economic gain. Figure 2-2 presents the time trends in burglary and motor vehicle theft rates (the latter scaled up by a factor of 2 to be comparable to burglary). We see a somewhat different pattern for burglary from that in Figure 2-1

OCR for page 13
 FACTORS CONTRIBUTING TO U.S. CRIME TRENDS 1,800 1,600 Burglary 1,40 0 Rate per 100K Population 1,20 0 1,000 800 Motor Vehicle Theft 600 40 0 200 1970 1975 1980 1985 1990 1995 2000 2005 2010 Year FIGURE 2-2 Burglary and motor vehicle theft, 1972-2006. Figure 2-2 for murder and robbery. Burglary has been on an almost steady downward trend since 1980. It is not clear why burglary, which shares with robbery the motive of economic gain, should have such a different pattern. It is pos- sible that many offenders began to substitute robbery, with its “one-stop shopping” characteristic, for burglary as the traditional fencing operations for stolen goods disappeared during the crack epidemic (Baumer et al., 1998). It is also possible that sanctions against burglary have increased faster than sanctions against robbery, thereby diminishing the difference between them and making robbery relatively more attractive as an illicit means of economic gain. The trend in motor vehicle theft, with a turning point in the early 1990s, is more similar to those for robbery and homicide than to the burglary trend, and it is consistent with qualitative accounts of stolen cars traded for drugs during the crack era (Jacobs, 1999) or for use by drug dealers to avoid having their own cars confiscated as forfeited assets. A clear need exists for research on the divergence between burglary and motor vehicle theft trends over the past 25 years.

OCR for page 13
0 UNDERSTANDING CRIME TRENDS LOOKING FOR GOOD LEADING INDICATORS Although some candidate explanations are more compelling than others, the factors underlying the recent crime trends in the United States, and especially those that might help to explain the abrupt reversals in trend we have documented, remain poorly understood (Levitt, 2004; Rosenfeld, 2004; Zimring, 2006). Given the social science community’s poor track record in explaining past crime trends, it is not surprising to find that efforts to forecast future changes are even less promising. Reliable forecasting requires either strong time-series predictors or knowledge of leading indi- cators that can be used to predict future changes in crime rates, such that knowledge of the indicator’s value at t0 yields an accurate prediction of the change in crime at t1, some later time. We consider the forecasting possibili- ties of several of the factors already mentioned and a few additional ones that appear to hold some promise at both the national and local levels. Demographic Trends As noted previously, demography provides one of the best leading indicators. On one hand, it is well established, and it can be forecast well into the future. It invokes the information contained in the well-known age-crime curves and in racial and ethnic differences in victimization and offending patterns. When there are no other comparably strong influences, demographic changes may provide the best prediction of future crime trends. On the other hand, we also have mentioned in earlier sections other impor- tant factors that can dominate the demographic effects. This is particularly true when the demographic changes are relatively slow. Indeed, during the sharp crime drop of the 1990s, age composition changes were trending in the wrong direction: the number of 18-year-olds in the U.S. population was increasing while crime rates were declining for other reasons. Age Composition The role of age composition can be assessed from Figure 2-3, which shows the number of people of each age in 2005. The strong effect of the baby boom is seen in the right-hand portion of the curve. There was a 30 per- cent increase in cohort size between 1945 and 1947 (the two cohorts were 60 and 58 years old, respectively, in 2005). Subsequent cohorts were increasing in size until the peak 1960 cohort (which was 45 years old in 2005). Look- ing at the cohorts between ages 0 and 20 one does not see any important changes in cohort sizes, with most of those cohorts varying around 4 million persons per cohort. Thus, changing age composition is not likely to provide a substantial influence on crime rates for the next 20 years.

OCR for page 13
 FACTORS CONTRIBUTING TO U.S. CRIME TRENDS 5 4 Number at Each Age 3 (Millions) 2 1 0 0 10 20 30 40 50 60 70 Ag e FIGURE 2-3 Demography: Age distribution of the U.S. population in 2005. Race and Ethnicity Figure 2-3, editable Because there are sizable differences in crime involvement among racial and ethnic groups, changes in their size might be important in affect- ing crime trends. We can assess the probable race-ethnic effects with the data in Table 2-1, which presents projected changes in the composition of the U.S. population by race and ethnicity in five-year intervals through age 25 (based on data in http://www.census.gov/ipc/www/usinterimproj/ usproj2000-2050.xls). The table shows that the growth rate in the white and black populations is generally quite slow (less than 1 percent per year for almost all age-year combinations), while the growth in the Hispanic population is somewhat greater (typically on the order of 1-2 percent per year). These aggregate growth rates are generally quite small and so are not likely to have a major effect on crime rates during a period of major change, such as the 1990s, when the homicide and robbery rates fell by about 5 percent per year, or between 1985 and 1991, when they rose by 3 to 4 percent per year. It is possible, of course, that during more limited periods or for particu- lar ages the demographic shifts could become important. Table 2-2 presents the projected trends for 15-year-olds as an illustration of that effect. We note that during the 2000-2005 period, both blacks (2.9 percent) and His-

OCR for page 13
 UNDERSTANDING CRIME TRENDS TABLE 2-1 Annual Percentage Change in U.S. White, Hispanic, and Black Populations by Age Over Five-Year Intervals, 2000-2020 Age White Hispanic Black 5 0.1 1.9 0.64 10 –0.6 1.9 –0.02 15 –0.6 2.5 0.36 20 –0.6 1.6 0.09 TABLE 2-2 Annual Percentage Change in U.S. White, Hispanic, and Black 15-Year-Olds Over Five-Year Intervals, 2000-2020 Years White Hispanic Black 2000-2005 0.5 4.5 2.9 2005-2010 –2.2 1.6 –2.1 2010-2015 –1.0 1.5 –1.2 2015-2020 0.5 2.4 1.7 panics (4.5 percent) had appreciably larger annual growth than over the entire 20-year period. This might well have introduced a demographic effect into the crime changes in recent years, as the 15-year-olds move toward the peak ages of the age-crime curve. But the rate of change for the later years is smaller for Hispanics and negative for blacks, so it is likely that any such demographic effect would be short and transient. Incarceration Another factor with some promise as a leading indicator for crime is the extent of incarceration. There is little question that incarceration at the levels used in the United States has a crime reduction effect, most specifi- cally through incapacitation. But that effect varies with crime type, and it is quite dubious for offenders engaged in illicit markets, like drug dealers, in which replacements can be recruited when offenders are sent to prison (Blumstein, 1993, 1995). Also, the effect will differ with the offender’s age (e.g., those in their 30s have the longest residual career length) and with the length of the sentence being served. Some policy analysts argue that incarceration is the dominant influence on crime, with the growth of incar- ceration during the 1990s crime drop given as a dramatic case in point. But incarceration was also increasing during the 1980s, when crime rates were going up. This highlights the fact that crime rates are affected by a

OCR for page 13
 FACTORS CONTRIBUTING TO U.S. CRIME TRENDS multiplicity of factors—some pushing them up and others pushing them down—and at any time one or another could be dominating the rest. It is the net sum of these factors that results in a net positive or negative effect on crime rates. Such considerations call for multivariate investigations of the impact of incarceration on crime rates. That research has, with exceptions, shown that crime rates decline with increases in incarceration, net of other influences (Levitt, 1996; Marvell and Moody, 1994; but see DeFina and Arvanites, 2002). Rosenfeld and Fornango (2007) estimate that rising incarceration rates accounted for about 19 percent of the decline in national robbery rates and 23 percent of the drop in burglary rates during the 1990s, controlling for the effects of economic conditions, growth in police per capita, changes in age and race composition, and lagged crime rates. These results are similar to those reported by Spelman (2006), Rosenfeld (2006a), and Levitt (2004). This convergence in results does not guarantee a similar effect under any other circumstances, but it does highlight the ability to make reason- able estimates of the effects of incarceration on recent U.S. crime trends. Using the elasticity estimates that derive from these analyses and the time lag between observed increases in imprisonment and crime reductions (gen- erally estimated as one year but sometimes longer), one should be able to anticipate future effects on crime as incarceration rates and related policies change. For example, given the recent decline in the net growth of incar- ceration, the large numbers of individuals being released from prison (about 700,000 per year), and potential difficulties in readjusting to civilian life, one might have expected some reduction of the incarceration effect on robbery and homicide over the past few years. Future research, however, should consider two limits on the relation- ship between incarceration and crime. First, if the crime reduction effects of incarceration are assumed to operate mainly through incapacitation, they are likely to be strongly age-graded. The crime rates of younger people, who have a comparatively low risk of incarceration, should not be affected as much as those of adults by aggregate changes in the incarceration rate, which largely reflects the incapacitation of offenders in their late 20s and 30s (again, the median age of prisoners is early 30s). A second condition limiting the crime reduction effects of imprison- ment concerns the diminishing effect of incapacitation as imprisonment rates increase. Research indicates that the effect of imprisonment on crime varies with the scale of incarceration. The crime reduction effects of impris- onment grow larger as incarceration rates increase and then level off and could well diminish (Canela-Cacho, Blumstein, and Cohen, 1997). There is some indication that additional expansion in incarceration may actually be associated with crime increases (Clear et al., 2003; Liedka, Piehl, and Useem, 2006).

OCR for page 13
 UNDERSTANDING CRIME TRENDS nality are all important determinants of individual delinquency and crimi- nality. Family-based crime prevention programs have been shown to reduce children’s antisocial behavior and arrests during adolescence. The family factors affecting delinquency and crime may be modifiable by investments in a wide array of social services, but especially in pre- and postnatal home visits and parent training programs, which demonstration projects have shown to be especially effective (Farrington, 2002). The availability of such services, even when supported by local funding, is particularly sensitive to federal social welfare investments. As federal budget deficits have grown in recent years, such services have been cut back and become more depen- dent on local financing, which has been under considerable strain in many urban areas, where such support is most needed. The same is true of more narrowly focused violence prevention programs, including those of proven effectiveness, such as the Blueprints program evaluated by the Center for the Study and Prevention of Violence at the University of Colorado (http:// www.colorado.edu/cspv/blueprints/index.html). A challenging research need is to link individual-level data on child- hood socialization to aggregate trends in social welfare investments, and both of these to crime trends. It should be possible in principle to integrate data from longitudinal studies of child and adolescent development with aggregate budgetary and crime data for those cities in which the longitu- dinal developmental studies have been conducted over an extended period (e.g., Pittsburgh, Rochester, Denver, Montreal). Until such multilevel studies are undertaken, one will not know to what extent the risk factors identi- fied in developmental research can serve as leading indicators of changes in crime rates or to what degree public investments in social services can help to ameliorate childhood risks for delinquency and crime. FUTURE RESEARCH NEEDS We have identified several factors that prior research suggests have been associated with changes in crime rates in the United States over the past several decades. These include demographic shifts, growth in incarceration, drug markets, and changing economic conditions. We have discussed other factors, such as policing innovations, firearm availability, street gangs, childhood socialization, and investments in social services that may influ- ence crime trends but for which the existing evidence is too fragmentary to develop accurate effect measures. Much remains to be learned about the factors affecting crime trends, including those we already know something about. For example, the crack markets were implicated in the rise of youth fire- arm violence during the late 1980s, and an important reason was because young people replaced the adult drug sellers who were sent to prison

OCR for page 13
 FACTORS CONTRIBUTING TO U.S. CRIME TRENDS (Blumstein, 1995). That interpretation is consistent not only with the rising imprisonment rates for adult drug dealers during the 1980s but with the ris- ing rates of drug arrests and gun violence among minority adolescents that occurred after 1985. The evidence for this explanation could be augmented by results from panel studies showing that the largest increases in youth firearm violence were concentrated in those cities with the largest increases in drug arrests of crack dealers. Those increases, in turn, should have hap- pened in those cities displaying the largest increases in the incarceration of adult drug sellers. Such evidence would further support a leading explana- tion of the upturn in violent crime during the 1980s that has important policy implications: an unanticipated negative consequence of the intensive sentencing policies initiated as part of the war on drugs was its contribution to the rise in youth violence. To take another example, we have argued that the strong economy of the 1990s contributed to the decline in violence. During the longest peace- time economic boom on record, tight labor markets were able to absorb minority youth who no longer could make money in the shrinking drug markets. The implication is that the economic expansion conditioned the effect on crime of the drop in demand for crack. In the absence of legitimate employment opportunities, more young people would have pursued other illegitimate opportunities for making money. Again, this story is compatible with several co-occurring trends at the national level in the 1990s, including falling unemployment rates among minority youth and declining demand for crack (Golub and Johnson, 1994). Stronger evidence, with direct rel- evance for employment policies, would come from studies showing that the impact of declining drug markets on crime reduction was strongest in those cities exhibiting the sharpest increases in minority youth employment and earnings. The Future of Crime Forecasting Developing sound empirical explanations of past crime trends is an important means of improving the capacity to make informative and reason- ably accurate forecasts of future changes. As approaches are developed to estimating and forecasting the factors contributing to crime trends, it is useful to recognize that there are few significant social or even natural phenomena for which there are good forecasts. For example, a leading group of weather forecasters inaccurately predicted a “very active” 2007 hurricane season. The group’s forecast for 2006 overpredicted hurricanes; the year before that, when Hurricane Katrina hit, they erred on the low side. Forecasts of when and where emerging tropical storms will land tend not to be very accurate (Merzer, 2007; see National Research Council, 2006, for a useful discussion of incorporating uncertainty into the dissemination of weather forecasts).

OCR for page 13
 UNDERSTANDING CRIME TRENDS The field of macroeconomics offers another example of considerable effort to develop forecasting models and abundant forecasting failures (Gross, 2007). Despite the large industry devoted to economic forecasts, one week saw the current and former chairmen of the Federal Reserve come out at the same time with strongly differing forecasts, one suggesting the possibility of a recession within the year and the other commenting on the current strength of the economy. Given the resources available and the experience they both bring, and given that the forecast extended for only one year, it is humbling—but also encouraging—to enter the challenge of forecasting crime. The encouragement comes not from the accuracy of weather or eco- nomic forecasts but from the seriousness of the efforts, stimulated no doubt by the strong economic interest in their forecasts. Criminologists are noto- rious for the inaccuracy of their crime forecasts; consider only the widely publicized prediction of a crime boom brought on by marauding “super predators” (Dilulio, 1995) issued just as crime rates began their historic plunge in the 1990s. The problem with such forecasts is not simply that they are wrong, but also that they are based on minimal systematic analysis. One therefore learns nothing from them. When meteorologists or econo- mists fail to accurately predict the next tropical storm or recession, they can acquire new knowledge about the conditions affecting the weather or economy, which can be used to enhance the data and refine the models used in making the forecasts. Opportunities for such self-correction are absent when forecasts are created in the interest of advocacy, with no opportunities for challenge and replication. Only with a large investment of resources can criminologists hope for their forecasting models to become as meaningful as those from economists, let alone meteorologists. National and Regional Estimates It is useful to differentiate efforts at generating national estimates, regional estimates, and local estimates for a particular city or neighborhood. For the national estimates, it is difficult at this point to identify any reliable leading indicators other than demographic shifts. Nevertheless, efforts to identify such indicators are desirable, at least in part because such forecasts could influence the level of federal financial support for policing and other local criminal justice initiatives. A measure of collective economic percep- tions from consumer surveys seems to be a strong contemporary correlate of changes in several crime types and may well be a leading indicator of some (Rosenfeld and Fornango, 2007). Similar considerations would apply in the search for multistate regional indicators. There are good reasons to believe that reliable regional indicators might be found because regions are generally more homogeneous than the nation as a whole. The consumer

OCR for page 13
 FACTORS CONTRIBUTING TO U.S. CRIME TRENDS sentiment data are available for the four major census regions. For both the nation and regions, one would also look to drug activity, particularly drugs that are sold in street markets or that start a rapid escalation of demand, as primary indicators of rising crime rates ahead. Local-Level Estimates Both economic and drug market indicators should also be evaluated for their contributions to crime forecasts at the neighborhood or city level. Local efforts could be more effectively targeted than national resources or policies, and so developing better estimates for local application would be particularly desirable. The consumer sentiment data are not available for cities or metropolitan areas, but the crime-forecasting capabilities of other economic indicators of local conditions, such as youth unemployment and wage rates, should be investigated. A useful research task would be to use traditional regression-based clustering models to aggregate a large number of cities into subgroups that display similar patterns in crime trends. Alter- natively, one might use trajectory analysis (Nagin, 2005) to aggregate into groups cities that have displayed similar crime trends. One could then look for leading indicators of the patterns for each of these trajectory groups. Because the different trajectory groups will have different patterns, there is a strong likelihood that different factors affect them. We anticipate that in the contemporary environment, drug markets, incarceration levels, and employment opportunities for unskilled young men are likely to be impor- tant factors affecting crime trends in the larger cities. Whether the same factors also help to explain the trends in smaller cities is a research ques- tion for which regression analysis, including interactions with city size, or trajectory analysis could well contribute. At the neighborhood level, crime, especially violent crime, is concen- trated in relatively few areas of the city, a pattern similar to the highly skewed distribution of serious offending across individuals (Chaiken and Chaiken, 1982). Researchers have begun to use trajectory methods at the neighbor- hood and even smaller levels of aggregation with some promising initial results (Griffiths and Chavez, 2004; Weisburd et al., 2004). Forecasting at this level poses special research challenges but also some distinctive oppor- tunities for acquiring information from individuals familiar with the local environment. Police, youth workers, social service providers, and neighbor- hood residents are often sensitive to changes in mood and activity patterns and signs of disorder that can serve as early warnings of an upturn in crime. Short-term forecasts of crime patterns at the neighborhood level, such as those recently produced for the Pittsburgh Police Department (Cohen, Gorr, and Olligschlaeger, 2007), also are likely to be of more immediate interest to police managers than forecasts of crime rates for the entire city.

OCR for page 13
 UNDERSTANDING CRIME TRENDS An exciting potential for forecasting at the local level lies in the rich individual and family data from long-standing longitudinal investigations of delinquent and antisocial behavior that are situated in several cities. The challenge is to evaluate the indicators that provide good predictions, some- times years ahead, of individual criminal involvement for their potential as leading indicators of neighborhood or city crime trends. This will require multilevel analyses that go beyond the now common practice of assessing “neighborhood effects” on individual criminal behavior by estimating the effects of aggregated individual propensities on community crime rates. Such research will necessitate bringing together researchers with quite different interests and skills into collaborative projects. The science of crime forecasting could be advanced significantly by incorporating findings from longitudinal research on individual criminal behavior into analyses of changes in crime rates over time. Building the Research Infrastructure The relevance of these proposals for future research on crime trends to assessments of crime control policy will be limited in the absence of a substantial upgrading in the nation’s capacity to monitor crime trends. We have already observed the divergent interpretations following reports of some recent crime increases, which stem in large part from the time delay between the availability of local crime data and the UCR’s dissemination of aggregate crime statistics. Such delays can provide an opportunity for advocacy groups to leap into the information breach with data of uncertain reliability. There is no technical reason why the recording and dissemina- tion of crime data cannot be as rapid as, say, the compilation and online dissemination of unemployment data by the Bureau of Labor Statistics (Rosenfeld, 2007b). As with many economic time series, the UCR crime data could be released on a quarterly and eventually a monthly basis, with dissemination of the annual data three months after the collection year a reasonable goal. More rapid dissemination, however, would lead to a need for more imputation to develop estimates for nonreporting agencies and require corresponding improvement in the methodology for developing those imputed estimates. One attempt to significantly enhance the data from the UCR was the introduction of the National Incident-Based Reporting System (NIBRS). Rather than relying merely on aggregate counts of incidents or of arrestees, this approach involved compiling detailed information on individual crime incidents, the perpetrators and the victims, the multiple offenses that occurred in the incident, and aggregating those data as needed to generate population counts and rates. Participation in NIBRS by local police depart- ments has still not exceeded 25 percent of the U.S. population, even though

OCR for page 13
 FACTORS CONTRIBUTING TO U.S. CRIME TRENDS the system has been in operation for over 20 years. It would be most desir- able to find ways to increase that participation in a major way to develop the rich data potentially available from the NIBRS approach. One method would be to tie federal funding of state and local crime control initiatives to participation in NIBRS, with some of that funding directed specifically to NIBRS implementation. The FBI is currently developing an incident-based data system called N-DEX that involves much richer detail on each incident. It is possible that the more detailed data, especially if disseminated more rapidly, could generate much greater participation than has been the case with NIBRS. But the NIBRS experience suggests that participation is likely to be even less extensive without additional incentives. Much more can be done to improve the current minimal efforts related to crime measurement and forecasting. The precision of crime estimates from the NCVS, which was conducted initially with a much larger sample and with more face-to-face interviewing, has eroded considerably because funding limitations have reduced the sample size and resulted in more tele- phone interviews, even as declining crime rates warranted larger samples to maintain statistical power. Also, the NCVS, which now regularly provides only national estimates of victimization experience, could well provide sub- national estimates, at least for the larger metropolitan areas (see Lauritsen and Schaum, 2005). It might also be able to provide some limited number of characteristics of each respondent’s census tract if those characteristics were modified with some random error to protect the respondents’ privacy. Doing so would permit linking socioeconomic characteristics to crime prevalence. Improving the nation’s capacity to monitor crime trends will require additional resources devoted to compiling, disseminating, and updating the data. The National Institute of Justice can play an important part in this process by establishing an ongoing research program devoted to analyzing crime trends. Building the infrastructure for understanding changes in crime rates over time is an important criminal justice policy priority and a major focus of more extensive investigations of crime trends emerging from this workshop. REFERENCES Anderson, Elijah. (1999). Code of the street: Decency, iolence, and the moral life of the inner city. New York: Norton. Arvanites, Thomas M., and Robert H. DeFina. (2006). Business cycles and street crime. Criminology, , 139-164. Baumer, Eric, Janet L. Lauritsen, Richard Rosenfeld, and Richard Wright. (1998). The influ- ence of crack cocaine on robbery, burglary, and homicide rates: A cross-city, longitudinal analysis. Journal of Research in Crime and Delinquency, , 316-340.

OCR for page 13
0 UNDERSTANDING CRIME TRENDS Blumstein, Alfred. (1993). Making rationality relevant: The American Society of Criminology presidential address. Criminology, , 1-16. Blumstein, Alfred. (1995). Youth violence, guns, and the illicit-drug industry. Journal of Crimi- nal Law and Criminology, , 10-36. Blumstein, Alfred. (2006). Disaggregating the violence trends. In Alfred Blumstein and Joel Wallman (Eds.), The crime drop in America (revised ed.). New York: Cambridge Uni- versity Press. Blumstein, Alfred, and Richard Rosenfeld. (1998). Explaining recent trends in U.S. homicide rates. Journal of Criminal Law and Criminology, , 1175-1216. Blumstein, Alfred, and Joel Wallman. (2006). The crime drop in America (revised ed.). New York: Cambridge University Press. Blumstein, Alfred, Jacqueline Cohen, and Harold Miller. (1980). Demographically disaggre- gated projections of prison populations. Journal of Criminal Justice, , 1-25. Braga, Anthony A. (2005). Hot spots policing and crime prevention: A systematic review of randomized controlled trials. Journal of Experimental Criminology, , 317-342. Canela-Cacho, Jose A., Alfred Blumstein, and Jacqueline Cohen. (1997). Relationship between the offending frequency (λ) of imprisoned and free offenders. Criminology, , 133-175. Chaiken, Jan, and Marcia Chaiken. (1982). Varieties of criminal behaior. (RAND Report No. R-2814-NIJ.) Santa Monica, CA: RAND Corporation. Clear, Todd R., Dina R. Rose, Elin Waring, and Kristen Scully. (2003). Coercive mobility and crime: A preliminary examination of concentrated incarceration and social disorganiza- tion. Justice Quarterly, 0, 33-64. Cohen, Jacqueline, Wilpen L. Gorr, and Andreas M. Olligschlaeger. (2007). Leading indica- tors and spatial interactions: A crime-forecasting model for proactive police deployment. Geographical Analysis, , 105-127. Cook, Philip J., and Jens Ludwig. (2006). The social costs of gun ownership. Journal of Public Economics, 0, 379-391. Cook, Philip J., and Gary A. Zarkin. (1985). Crime and the business cycle. Journal of Legal Studies, , 115-128. Cork, Daniel. (1999). Examining space-time interaction in city-level homicide data: Crack markets and the diffusion of guns among youth. Journal of Quantitatie Criminology, , 379-406. Curtin, Richard T. (2002). Sureys of consumers: Theory, methods, and interpretation. Paper presented at the September 30, 2002 meeting of the National Association for Business Economics, Washington, DC. Curtin, Richard T. (2003). Unemployment expectations: The impact of private information on income uncertainty. Reiew of Income and Wealth, , 539-554. Decker, Scott H., and Barrik van Winkle. (1996). Life in the gang. New York: Cambridge University Press. DeFina, Robert H., and Thomas M. Arvanites. (2002). The weak effect of imprisonment on crime: 1971-1992. Social Science Quarterly, , 635-653. Dilulio, John J. (1995, November 27). The coming of the super predators. The Weekly Standard. Donohue, John J., and Steven D. Levitt. (2001). The impact of legalized abortion on crime. Quarterly Journal of Economics, , 379-420. Donohue, John J., and Steven D. Levitt. (2004). Further evidence that legalized abortion lowered crime: A reply to Joyce. Journal of Human Resources, , 29-49. Easterlin, Richard. (1987). Birth and fortune: The impact of numbers on personal welfare (2nd ed.). Chicago: University of Chicago Press.

OCR for page 13
 FACTORS CONTRIBUTING TO U.S. CRIME TRENDS Eck, John E., and Edward R. Maguire. (2006). Have changes in policing reduced violent crime? An assessment of the evidence. In Alfred Blumstein and Joel Wallman (Eds.), The crime drop in America (revised ed.). New York: Cambridge University Press. Egley, Arlen, and Christina E. Ritz. (2006). Highlights of the 00 National Youth Gang Sur- ey. Fact Sheet 2006-01. Washington, DC: U.S. Department of Justice, Office of Juvenile Justice and Delinquency Prevention. Fagan, Jeffrey, and Deanna L. Wilkinson. (1998). Guns, youth violence and social identity in inner cities. Crime and Justice, , 105-188. Farrington, David P. (2002). Families and crime. In James Q. Wilson and Joan Petersilia (Eds.), Crime: Public policies for crime control. Oakland, CA: ICS Press. Freeman, Richard B. (1996). Why do so many young American men commit crimes and what might we do about it? Journal of Economic Perspecties, 0, 25-42. Golinelli, Roberto, and Giuseppi Parigi. (2004). Consumer sentiment and economic activity: A cross-country comparison. Journal of Business Cycle Measurement and Analysis, , 147-170. Golub, Andrew, and Bruce D. Johnson. (1994). A recent decline in cocaine use among youthful arrestees in Manhattan (1987-1993). American Journal of Public Health, , 1250-1254. Griffiths, Elizabeth, and Jorge M. Chavez. (2004). Communities, street guns, and homicide trajectories in Chicago, 1980-1995: Merging methods for examining homicide trends across space and time. Criminology, , 941-978. Grogger, Jeffrey. (2006). An economic model of recent trends in violence. In Alfred Blumstein and Joel Wallman (Eds.), The crime drop in America (revised ed.). New York: Cambridge University Press. Gross, Daniel. (2007, March 4). The forecast for the forecasters is dismal. New York Times. Harcourt, Bernard E., and Jens Ludwig. (2006). Broken windows: New evidence from New York City and a five-city social experiment. Uniersity of Chicago Law Reiew, , 271-320. Hemenway, David. (2004). Priate guns, public health. Ann Arbor: University of Michigan Press. Jacobs, Bruce A. (1999). Dealing crack: The social world of streetcorner selling. Boston: Northeastern University Press. Jacobs, Bruce A. (2000). Robbing drug dealers. Hawthorne, NY: Aldine. Johnson, Bruce D., Andrew Golub, and Eloise Dunlap. (2006). The rise and decline of hard drugs, drug markets, and violence in inner-city New York. In Alfred Blumstein and Joel Wallman (Eds.), The crime drop in America (revised ed.). New York: Cambridge University Press. Joyce, Theodore J. (2004). Did legalized abortion lower crime? Journal of Human Resources, , 1-28. Kelling, George, and William H. Sousa, Jr. (2001). Do police matter? An analysis of the impact of New York City’s police reforms. Manhattan Institute Ciic Report, 22(December). Available: http://www.manhattan-institute.org/pdf/cr_22.pdf [accessed August 2008]. Kennedy, David M., Anthony A. Braga, Anne M. Piehl, and Elin J. Waring. (2001). Reduc- ing gun iolence: The Boston Gun Project’s Operation Ceasefire. (National Institute of Justice Research Report.) Washington, DC: U.S. Department of Justice. Kleck, Gary. (1997). Targeting guns: Firearms and their control. New York: Aldine. Kleck, Gary, and Ted Chiricos. (2002). Unemployment and property crime: A target-specific assessment of opportunity and motivation as mediating factors. Criminology, 0, 649-680. Klein, Malcolm W. (1995). The American street gang: Its nature, prealence, and control. New York: Oxford University Press.

OCR for page 13
 UNDERSTANDING CRIME TRENDS LaFree, Gary. (1998). Losing legitimacy: Street crime and the decline of institutions in America. Boulder, CO: Westview. Lauritsen, Janet L., and Robin J. Schaum. (2005). Crime and ictimization in the three largest metropolitan areas, 0-. Washington, DC: U.S. Department of Justice. Levitt, Steven D. (1996). The effect of prison population size on crime rates: Evidence from prison overcrowding litigation. Quarterly Journal of Economics, , 319-352. Levitt, Steven D. (2002). Deterrence. In James Q. Wilson and Joan Petersilia (Eds.), Crime: Public policies for crime control. Oakland, CA: ICS Press. Levitt, Steven D. (2004). Understanding why crime fell in the 1990s: Four factors that explain the decline and six that do not. Journal of Economic Perspecties, , 163-190. Levitt, Steven D., and Stephen J. Dubner. (2005). Freakonomics: A rogue economist explores the hidden side of eerything. New York: William Morrow. Liedka, Raymond V., Anne Morrison Piehl, and Bert Useem. (2006). The crime control effect of incarceration: Does scale matter? Criminology and Public Policy, , 245-276. Marvell, Thomas B., and Carlisle E. Moody. (1994). Prison population and crime reduction. Journal of Quantitatie Criminology, 0, 109-139. Merzer, Martin. (2007, April 4). Strong hurricane season is forecast. St. Louis Post-Dispatch, A2. Messner, Steven F., Glenn D. Deane, Luc Anselin, and Benjamin Pearson-Nelson. (2005). Locating the vanguard in rising and falling homicide rates across U.S. cities. Criminol- ogy, , 661-696. Messner, Steven F., Sandro Galea, Kenneth J. Tardiff, Melissa Tracy, Angela Bucciarelli, Tinka Markham Piper, Victoria Frye, and David Vlahov. (2007). Policing, drugs, and the homi- cide decline in the 1990s. Criminology, (2), 385-414. Nagin, Daniel. (2005). Group-based modeling of deelopment. Cambridge, MA: Harvard University Press. Nasar, Sylvia. (1998, May 9). U.S. jobless rate plunges to 4.3%, lowest since 1970. New York Times, A1, B3. Nasar, Sylvia, and Kirsten B. Mitchell. (1999, May 23). Booming job market draws young black men into fold. New York Times, 1, 21. National Research Council. (2005). Firearms and iolence: A critical reiew. Committee to Improve Research Information and Data on Firearms, Charles F. Wellford, John V. Pepper, and Carol V. Petrie (Eds.). Committee on Law and Justice. Division of Behavioral and Social Sciences and Education. Washington, DC: The National Academies Press. National Research Council. (2006). Completing the forecast: Characterizing and communi- cating uncertainty for better decisions using weather and climate forecasts. Committee on Estimating and Communicating Uncertainty in Weather and Climate Forecasts. Washington, DC: The National Academies Press. Needleman, Herbert. (1995). Environmental lead and children’s intelligence. British Medical Journal, 0, 6991. Nevin, Rick. (2000). How lead exposure relates to temporal changes in IQ, violent crime, and unwed pregnancy. Enironmental Research, A., 1-22. O’Brien, Robert M., Jean Stockard, and Lynne Isaacson. (1999). The enduring effects of cohort characteristics on age-specific homicide rates: 1960-1995. American Journal of Sociology, 0, 1061-1095. Peterson, Dana, Terrance J. Taylor, and Finn A. Esbensen. (2004). Gang membership and violent victimization. Justice Quarterly, , 794-815. Police Executive Research Forum. (2006). A gathering storm: Violent crime in America. Wash- ington, DC: Author. Available: http://www.policeforum.org/upload/Gathering-Storm- PRINT-Final_110473745_1027200610304.pdf [accessed August 2008].

OCR for page 13
 FACTORS CONTRIBUTING TO U.S. CRIME TRENDS Police Executive Research Forum. (2007). Violent crime in America:  months of alarm- ing trends. Washington, DC: Author. Available: http://www.policeforum.org/upload/ Violent%20Crime%20Report%203707_140194792_392007143035.pdf [accessed August 2008]. Reyes, Jessica Walpow. (2007). Enironmental policy as social policy? The impact of child- hood lead exposure on crime. (NBER Working Paper No. 13097.) Cambridge, MA: National Bureau of Economic Research. Available: http://www3.amherst.edu/~jwreyes/ papers/LeadCrimeNBERWP13097.pdf [accessed August 2008]. Rose, Dina R., and Todd R. Clear. (1998). Incarceration, social capital and crime: Examining the unintended consequences of incarceration. Criminology, , 441-479. Rosenfeld, Richard. (2004, February). The case of the unsolved crime decline. Scientific American, 82-89. Rosenfeld, Richard. (2006a). Patterns in adult homicide: 1980-1995. In Alfred Blumstein and Joel Wallman (Eds.), The crime drop in America (revised ed.). New York: Cambridge University Press. Rosenfeld, Richard. (2006b). Connecting the dots: Crime rates and criminal justice evaluation research. Journal of Experimental Criminology, , 309-319. Rosenfeld, Richard. (2007a). Explaining the divergence between UCR and NCVS aggravated assault trends. In James P. Lynch and Lynn A. Addington (Eds.), Understanding crime statistics: Reisiting the diergence of the NCVS and the UCR. New York: Cambridge University Press. Rosenfeld, Richard. (2007b). Transfer the Uniform Crime Reporting Program from the FBI to the Bureau of Justice Statistics. Criminology and Public Policy, (4), 825-833. Rosenfeld, Richard, and Robert Fornango. (2007). The impact of economic conditions on robbery and property crime: The role of consumer sentiment. Criminology, (4), 735-769. Rosenfeld, Richard, Robert Fornango, and Eric Baumer. (2005). Did Ceasefire, Compstat, and Exile reduce homicide? Criminology and Public Policy, , 419-450. Rosenfeld, Richard, Eric Baumer, and Steven F. Messner. (2007). Social trust, firearm preva- lence, and homicide. Annals of Epidemiology, , 119-125. Rosenfeld, Richard, Robert Fornango, and Andres Rengifo. (2007). The impact of order- maintenance policing on New York City robbery and homicide rates: 1988-2001. Crimi- nology, , 355-383. Sheley, Joseph F., and James D. Wright. (1995). In the line of fire: Youths, guns, and iolence in urban America. Hawthorn, NY: Aldine. Spelman, William. (2006). The limited importance of prison expansion. In Alfred Blumstein and Joel Wallman (Eds.), The crime drop in America (revised ed.). New York: Cambridge University Press. Thornberry, Terrence P., Marvin D. Krohn, Alan J. Lizotte, Carolyn A. Smith, and Kimberly Tobin. (2003). Gangs and delinquency in deelopmental perspectie. New York: Cam- bridge University Press. U.S. Census Bureau. (2006). Statistical abstract of the United States: 00. Washington, DC: U.S. Department of Commerce. Available: http://www.census.gov/compendia/statab/ 2008edition.html [accessed October 2008]. Weisburd, David, Shawn Bushway, Cynthia Lum, and Sue-Ming Yang. (2004). Trajectories of crime at places: A longitudinal study of street segments in the city of Seattle. Criminol- ogy, , 283-321. Wilson, James Q. (2002). Crime and public policy. In James Q. Wilson and Joan Petersilia (Eds.), Crime: Public policies for crime control (pp. 537-557). Oakland, CA: ICS Press. Zimring, Franklin E. (2006). The great American crime decline. New York: Oxford University Press.

OCR for page 13